Node C13: Free Energy / Active Inference
Node C13: Free Energy / Active Inference
C13 — Free Energy / Active Inference { "id": "C13", "claim": "Self-organizing systems (from cells to brains) act to minimize variational free energy — a quantity bounding the surprise of sensory states — effectively making Bayesian inferences about their environment through action and perception.", "domain": ["neuroscience", "machine_learning", "theoretical biology", "psychiatry"], "pattern": ["free_energy_principle", "active_inference", "variational_Bayes", "predictive_coding"], "mechanism": "Variational free energy F = E_q[ln q(s) - ln p(o,s)] upper-bounds surprise (-ln p(o)). Systems minimize F by either (a) updating internal models (perception/inference) or (b) changing the world to match predictions (action). Under Laplace/Gaussian assumptions, this reduces to predictive coding: error = prediction - observation, minimized hierarchically.", "scale": "cellular → organism", "claim_tier": "T2", "sources": [ "Helmholtz, H. von (1867). Handbuch der Physiologischen Optik. Voss. [Perception as unconscious inference.]", "Friston, K. (2005). 'A Theory of Cortical Responses.' Phil. Trans. R. Soc. B, 360, 815-836.", "Friston, K. (2010). 'The Free-Energy Principle: A Unified Brain Theory?' Nature Reviews Neuroscience, 11, 127-138.", "Rao, R.P.N. & Ballard, D.H. (1999). 'Predictive Coding in the Visual Cortex.' Nature Neurosci., 2(1), 79-87." ], "dual": "None intrinsic — the dual would be a system that maximizes surprise (actively seeks chaos), which is pathological.", "falsifier": "An adaptive agent that provably does not reduce prediction error (or its bound) over time, yet survives and adapts comparably to predictive agents; or evidence that the free energy formalism cannot be operationalized with independent parameters.", "rival_frame": "FEP is unfalsifiable. Because any behavior can be described as minimizing some free energy functional post hoc, the principle predicts nothing independently. It is a mathematical tautology dressed as a theory — the Ptolemaic epicycles of neuroscience. Predictive coding is real and useful; the FEP as grand unification is not.", "independence_check": "MODERATE. Helmholtz (19th c. physiology) originated perception-as-inference from optics and eye movement studies. Rao & Ballard (1999, computational neuroscience) developed predictive coding independently from hierarchical Bayesian models. Friston (2005+, UCL) synthesized these into the Free Energy Principle. There is clear lineage from Helmholtz to Friston; the independence is in the computational instantiation, not the core insight.", "pattern_type": "energetic", "maps_to_axiom": ["A3", "A2"] }
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